More than trees, do we need a complex perspective for sustainable forest management?

TL;DR

This paper emphasizes the importance of considering systemic complexity in forest management, demonstrating how complexity metrics can serve as indicators of forest health and conservation status through case studies and data analysis.

Contribution

It introduces an informational framework to measure forest systemic complexity and shows its relevance for conservation and management decisions.

Findings

Complexity can be quantified using an informational framework.

Criticality state (1/f noise) indicates systemic complexity.

Lower complexity correlates with perturbed, less conserved forests.

Abstract

Forests are complex systems, and it is necessary to include this characteristic in every forest definition, in order to consider the restriction that this imposes in terms of prediction and control. This lost of predictability and controllability should be incorporated in every Environmental Impact Assessment or management program. We present two case-studies located in Mexico and one in the US to illustrate three relevant indicators of complexity. First, we introduce an informational framework to measure the Zoquiapan forest systemic complexity. Then, we analyze complexity changes among different types of forest and management systems, related with spatial distributions, using data from a floristic study in the Montes Azules National Park. Finally, we analyze time series of $CO_{2}$ fluctuations taken from AMERIFLUX data bases. Our results show firstly that it is possible to measure the systemic complexity of different forests, characteized by a criticality state (1/f noise) which has been proposed as a finger print of complexity. And secondly, that this characteristic can be used as a proxy of their state of conservation, where the lowest complexity values are found in perturbed areas showing the relevance of the concept and its measurement for forest conservation and management.